PROJECT SUMMARY/ ABSTRACT Basal cell carcinoma (BCC) is the number one cancer diagnosed in the US each year and accounts for more cases than all other cancers combined.1,2 Most BCCs are not dangerous, as they typically grow slowly and rarely metastasize or affect quality of life. Because cumulative exposure to ultraviolet radiation from the sun is a major cause of these lesions, BCCs are considered a non-lethal disease of aging, with the vast majority occurring in people 65 years or older. Despite the low risk BCCs present to patients, in the US all lesions are usually treated. Though existing treatments are effective,3,4 post treatment complications are common; in one prospective cohort study 27% of patients reported a problem after a procedure.5 Moreover, over 100,000 BCCs are treated annually in persons who ultimately die within one year of unrelated causes.6 For patients near the end of life, who often manage multiple health issues, treating these lesions may expose them to the associated medical risks with little potential benefit.7 There is a pressing need to reduce over-treatment and instead develop safe and effective active surveillance methods for low risk BCC in older patients. This research aims to fundamentally change the current ?one size fits all? standard of care for treatment of BCCs, which is particularly problematic for older adults.6,8,9 The goal of this application is to develop a mobile app for safe, home-based active surveillance of low risk basal cell carcinomas (BCCs). We hypothesize that home-based active surveillance of low risk BCCs would reduce unnecessary procedures, complications and burdensome clinic visits in patients whose BCCs are not changing, while ensuring that patients whose BCCs grow or become symptomatic receive prompt care. For the first step of the proposed research, we will refine an existing artificial intelligence algorithm and mobile app to optimize it for at-home active surveillence use for older adults with low-risk BCC. We will then conduct pre-testing with a small group of patients and caregivers (n=15) to iteratively improve the app and ensure usability. Finally, we will compare the data collected via the app to that collected during routine clinical visits. Over a 9-month period, we will follow participants (n=30) with low-risk BCC who have selected an active surveillance option. We will collect data monthly through the app, and every 3 months through in-person clinic visits. We will evaluate patient satisfaction and clinical course to determine the feasibility of using a mobile app for active surveillance of low-risk BCC.